Consistency Model
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A Consistency Model is a system contract for data consistency.
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- Example(s):
- See: Linear Continuum, Distributed Computing, Distributed Shared Memory, Filesystem, Database, Optimistic Replication, Web Caching, Consistent, Memory Semantics (Computing), Sequential Consistency, Undecidable Problem, ACID.
References
2016
- (Wikipedia, 2016) ⇒ http://en.wikipedia.org/wiki/consistency_model Retrieved:2016-1-5.
- In computer science, consistency models are used in distributed systems like distributed shared memory systems or distributed data stores (such as a filesystems, databases, optimistic replication systems or Web caching). The system supports a given model if operations on memory follow specific rules. The data consistency model specifies a contract between programmer and system, wherein the system guarantees that if the programmer follows the rules, memory will be consistent and the results of memory operations will be predictable.
High level languages, such as C++ and Java, partially maintain the contract by translating memory operations into low-level operations in a way that preserves memory semantics. To hold to the contract, compilers may reorder some memory instructions, and library calls such as
pthread_mutex_lock()encapsulate required synchronization. Verifying sequential consistency is undecidable in general, even for finite-state cache-coherence protocols. Consistency models define rules for the apparent order and visibility of updates, and it is a continuum with tradeoffs.
- In computer science, consistency models are used in distributed systems like distributed shared memory systems or distributed data stores (such as a filesystems, databases, optimistic replication systems or Web caching). The system supports a given model if operations on memory follow specific rules. The data consistency model specifies a contract between programmer and system, wherein the system guarantees that if the programmer follows the rules, memory will be consistent and the results of memory operations will be predictable.